Clover Health (Nasdaq: CLOV) is a physician enablement company focused on seniors who have historically lacked access to affordable, high-quality healthcare

We aim to provide great care, in a sustainable way, by having a business model built around improving medical outcomes while lowering avoidable costs. We do this while taking a holistic approach to understanding the health needs and social risk factors of those under our care. This strategy is underpinned by our proprietary software platform, the Clover Assistant, which is designed to aggregate patient data from across the health ecosystem to support clinical decision-making by presenting physicians and other providers with real-time, personalized recommendations at the point of care.

Making care more accessible is at the heart of our business, and we believe patients should have the freedom to choose their doctors. We offer affordable Medicare Advantage plans with extensive benefits, provide primary care physicians with the Clover Assistant, and also make comprehensive home-based care available via the Clover Home Care program.

You will serve as the Subject Matter Expert (SME) for clinical data completeness and effectiveness at Counterpart Health. Sitting within the Data Products pillar, this role owns the end-to-end understanding of our clinical data lifecycle: where data comes from, where it breaks down, and how each vendor or integration pathway performs across our customer markets. Your analysis will directly shape vendor strategy, facility targeting, and data pipeline investments, thus ensuring that the clinical evidence our care teams depend on is consistently available and trustworthy.

As a Data Analyst, you will:

Proactively identify and monitor which healthcare facilities consistently generate high-quality, usable clinical documents (e.g., EHRs, discharge summaries, procedure notes) to precisely locate and quantify data gaps.

Conduct deep-dive analyses by mapping and correlating facility-specific data across disparate sources like structured claims, clinical care summaries (CCDAs), and ADT messages to uncover systematic patterns of missingness, latency,

Experience with TEFCA/QHIN frameworks and evolving national interoperability standards.

Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2).

Background in value-based care, population health, or clinical data operations.

Experience with claims-clinical data reconciliation (e.g., matching EOBs to clinical encounter records).

Comfort working with Python or similar tools for data manipulation and automation. or incongruence in clinical records.

Establish and maintain clear, transparent reporting on ADT coverage across key geographic, organizational, and technological dimensions (e.g., by county, facility, and underlying EMR system).

Based on rigorous analysis of data flow and quality, recommend and guide the implementation of optimal technical configurations for existing data vendors (e.g., Bamboo Health, PCC, Experian, HSX).

Conduct comprehensive evaluations and proof-of-concepts for potential new data integration technologies (e.g., Kno2 vs. Particle Health) to assess viability, quality improvements, and strategic fit.

Systematically determine the existence and completeness of documentation associated with specific patient visits or encounters.

Develop a data-driven framework for prioritizing facility targets for direct data acquisition, assessing impact, cost-effectiveness, and technical feasibility.

Inform and guide vendor strategy around national initiatives such as TEFCA and QHIN adoption, ensuring Counterpart Health is positioned for compliant, high-quality data exchange.

Partner cross-functionally with Product Managers to define data requirements, Engineers to implement reliable pipelines, and Clinical teams to validate data quality and clinical utility.

Act as a critical liaison to identify and remove operational and technical bottlenecks, ensuring a predictable, scalable, and reliable clinical data flow across all customer markets.

You should get in touch if you have:

2+ years of hands-on data analytics experience, with direct exposure to healthcare data interoperability

Strong hands-on experience with healthcare data standards: HL7, CCDA, and ADT messages.

Proficiency in SQL and comfort working with large, complex datasets (claims, clinical logs, interoperability data).

Background in analyzing interoperability networks (e.g., Carequality, CommonWell, eHealthExchange) or HIE integrations.
Skilled at data visualization and able to present complex findings to both technical and non-technical stakeholders.

Strong investigative mindset, i.e., you enjoy digging into the “why” behind missing data and diverging metrics.

Self-directed and able to manage multiple analytical projects (vendor comparisons, visit-level reconciliation) without constant supervision.

Preferred Qualifications:

Experience with TEFCA/QHIN frameworks and evolving national interoperability standards.

Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2).

Background in value-based care, population health, or clinical data operations.

Experience with claims-clinical data reconciliation (e.g., matching EOBs to clinical encounter records).

Comfort working with Python or similar tools for data manipulation and automation.